Franklin Jessica M, Krumme Alexis A, Shrank William H, Matlin Olga S, Brennan Troyen A, Choudhry Niteesh K
1620 Tremont St, Ste 3030, Boston, MA 02120. E-mail:
Am J Manag Care. 2015 Sep 1;21(9):e537-44.
To evaluate the ability of initial medication dispensings to predict long-term patterns of adherence.
A retrospective cohort study of statin initiators enrolled in a Medicare Part D drug plan from CVS Caremark from 2005 to 2008.
We used group-based trajectory models to classify patients into 6 adherence trajectories based on patterns of statin filling over the year following therapy initiation. Baseline clinical characteristics and indicators of statin filling during the first 2 to 4 months following initiation were used to predict adherence trajectory in logistic regression models, separately within strata of the days' supply of the initial statin dispensing. Cross-validation was used to measure predictive accuracy of models in data not used for model estimation.
Among 77,703 statin initiators, prediction using baseline variables only was poor (cross-validated C statistic ≤ 0.61). When using 3 months of initial adherence to predict trajectory, prediction was greatly improved among patients with an index supply ≤30 days (0.62 ≤ C ≤ 0.91). With 4 months of initial adherence in the model, prediction was strong for all patients (C ≥ 0.72), especially for the best and worst trajectories (C = 0.90 and 0.94, respectively, in patients with an index supply ≤ 30 days; and C = 0.83 and 0.90, respectively, in patients with an index supply > 30 days).
Initial filling behavior strongly predicted future adherence trajectory. Predicting adherence trajectories may facilitate better targeting of interventions to patients most likely to benefit.
评估初始药物配药预测长期依从模式的能力。
一项对2005年至2008年参加CVS Caremark医疗保险D部分药物计划的他汀类药物起始使用者的回顾性队列研究。
我们使用基于组的轨迹模型,根据治疗开始后一年中他汀类药物的配药模式,将患者分为6种依从轨迹。在逻辑回归模型中,使用基线临床特征和起始后最初2至4个月内他汀类药物配药指标来预测依从轨迹,分别在初始他汀类药物配药供应天数的各层内进行。交叉验证用于测量模型在未用于模型估计的数据中的预测准确性。
在77703名他汀类药物起始使用者中,仅使用基线变量进行预测效果较差(交叉验证C统计量≤0.61)。当使用最初3个月的依从性来预测轨迹时,对于索引供应量≤30天的患者,预测有了很大改善(0.62≤C≤0.91)。模型中纳入最初4个月的依从性后,对所有患者的预测都很强(C≥0.72),尤其是对于最佳和最差轨迹(索引供应量≤30天的患者中C分别为0.90和0.94;索引供应量>30天的患者中C分别为0.83和0.90)。
初始配药行为强烈预测未来的依从轨迹。预测依从轨迹可能有助于更好地将干预措施针对最可能受益的患者。